The present invention relates to a tire design method.
When a pneumatic tire is designed, a design plan satisfying performance requirements is made based on knowledge of the related art, experiences, and limitations on designing. One approach for verification of the design is to check whether the performance requirements are satisfied or not using a structural analysis. When it is revealed at this stage that the performance requirements are not satisfied, the design is corrected, and a structural analysis is conducted again to verify the design. This process is repeated until the performance requirements are satisfied, and a design plan is thereby finalized.
According to the design method in the related art, no guarantee is given on whether a design plan finalized within a range set based on design limitations provides optimal values or not. Since the method involves the process of repeating designing, structural analysis, and re-designing, a design task will require an enormous amount of time. Under the circumstance, various methods for optimizing a tire through numerical optimizations have been proposed in an intention to allow efficient designing (see U.S. Pat No. 5,710,718A, U.S. Pat. No. 6,230,112B1, U.S. Pat. No. 6,531,012B2, Japanese Patent Laid-Open No. JP-A-2005-008011).
No quantitative understanding has been reached yet on the relationship between characteristics of a pneumatic tire and a tire structure such as a tire sectional shape including internal structures and a property of the material of a tire component, and the shape of a tread pattern formed on a tread surface. Therefore, when a pneumatic tire is designed, it is a common practice to decide the structure of the tire first and to design a shape of a tread pattern thereafter. That is, the tire structure and the tread pattern shape are optimized separately. Thus, no attention has been paid for finding of an optimal combination of a tire structure and a tread pattern shape.
In U.S. Pat. No. 5,710,718A, design variables for numerical optimizations are listed, including a function representing the shape of a carcass line or the like, a variable representing a gauge distribution of a tire rubber member, e.g., a gauge distribution of a bead filler, a variable representing a structure of a belt portion, e.g., the angle of each belt layer, and a variable representing a pattern shape such as a block shape. The document describes that at least one of the design variables is included in the optimizations. However, the document includes no specific mention on use of a variable associated with a tire structure and a variable associated with a tread pattern shape as design variables in conjunction with each other. Let us assume that it is suggested to perform optimization using a variable associated with a tire structure and a variable associated with a tread pattern shape as design variables in conjunction with each other. Even in such a case, the optimization will result in a great computational cost and will not necessarily allow designing to be carried out efficiently when the optimization involves what is called strong coupling, i.e., when the optimization is carried out using both of the variables as design variables in conjunction with each other.